Production-grade Freqtrade fork for algorithmic trading on Hyperliquid. Multi-bot OHLCV/pairlist caching, PlateauSampler hyperopt, walk-forward with CPCV, custom hyperopt losses, liquidation detection, 32+ enhancements. Includes showcase strategies. Maintained by Freqtrade France.

Python backtesting engine for US equity strategies. Point-in-time survivorship-free universes, Monte Carlo (+ block-bootstrap) & Walk-Forward Analysis, advanced position sizing, data-quality validation, intraday, regime heatmaps, PDF tearsheets, and ML-ready trade export. Five data providers — free with Yahoo Finance, no API key required.

Kiploks Trading Robustness Engine is an open-source TypeScript engine for deterministic backtest and walk-forward analysis (WFA) of algorithmic trading strategies, published as @kiploks/engine-* packages under Apache 2.0.

Freqtrade integration for Kiploks: crypto strategy backtest and robustness analytics.

Multi-asset portfolio backtesting engine for Python. Weights-based strategies, walk-forward analysis, and comprehensive metrics.

Validation-first backtesting harness for trading strategies on n8n + LLMs — walk-forward / OOS / Monte-Carlo, creator≠verifier, realistic costs. A methodology case study: most backtests lie; this one is built to make it hard to fool yourself.

Systematic pairs trading strategy on cointegrated US equities — Engle-Granger/Johansen cointegration screening, z-score mean-reversion signal, event-driven backtest with strict anti-look-ahead discipline, VaR/ES risk metrics.

Deterministic crypto/FX backtesting + validation engine that catches overfitting, lookahead, and fantasy costs. Its own research record: everything rejected. Paper-only.

Walk-forward backtest harness ranking 50 academically-sourced trading signals across a full history and a stress window

Modular research lab for market regime modeling, walk-forward strategy evaluation, and manual trading decision support.

Systematic quantitative research framework focused on strategy validation, robustness testing, risk analysis, and performance evaluation.

Markowitz mean-variance optimization with out-of-sample and walk-forward validation on 20 US equities. When Markowitz fails: out-of-sample testing shows naive 1/N beats mean-variance optimization on 20 US stocks.

Crypto trading strategy robustness score, backtest validation, and risk metrics. OctoBot integration

Six-phase quant research program: pre-registered, walk-forward, honestly disproving a +$28k backtest edge across ~10 years and 3 instruments

Reproducible Julia laboratory for market regimes, risk metrics and walk-forward validation

Cost-aware backtesting & walk-forward validation for Binance spot — a study in honest evaluation, not a performance claim